--- examples/common.h	2025-10-31 16:34:53
+++ ../non_submodule_llamafile/whisper.cpp/common.h	2025-10-31 16:53:51
@@ -1,153 +1,26 @@
+// -*- mode:c++;indent-tabs-mode:nil;c-basic-offset:4;tab-width:8;coding:utf-8 -*-
+// vi: set et ft=cpp ts=4 sts=4 sw=4 fenc=utf-8 :vi
+
 // Various helper functions and utilities
 
 #pragma once
 
 #include <string>
-#include <map>
 #include <vector>
-#include <random>
 #include <thread>
-#include <ctime>
 #include <fstream>
 
+#include "llamafile/xterm.h"
+
 #define COMMON_SAMPLE_RATE 16000
 
 //
-// GPT CLI argument parsing
-//
-
-struct gpt_params {
-    int32_t seed         = -1;   // RNG seed
-    int32_t n_threads    = std::min(4, (int32_t) std::thread::hardware_concurrency());
-    int32_t n_predict    = 200;  // new tokens to predict
-    int32_t n_parallel   = 1;    // number of parallel streams
-    int32_t n_batch      = 32;   // batch size for prompt processing
-    int32_t n_ctx        = 2048; // context size (this is the KV cache max size)
-    int32_t n_gpu_layers = 0;    // number of layers to offlload to the GPU
-
-    bool ignore_eos = false; // ignore EOS token when generating text
-
-    // sampling parameters
-    int32_t top_k          = 40;
-    float   top_p          = 0.9f;
-    float   temp           = 0.9f;
-    int32_t repeat_last_n  = 64;
-    float   repeat_penalty = 1.00f;
-
-    std::string model      = "models/gpt-2-117M/ggml-model.bin"; // model path
-    std::string prompt     = "";
-    std::string token_test = "";
-
-    bool    interactive      = false;
-    int32_t interactive_port = -1;
-};
-
-bool gpt_params_parse(int argc, char ** argv, gpt_params & params);
-
-void gpt_print_usage(int argc, char ** argv, const gpt_params & params);
-
-std::string gpt_random_prompt(std::mt19937 & rng);
-
-//
-// Vocab utils
-//
-
-std::string trim(const std::string & s);
-
-std::string replace(
-        const std::string & s,
-        const std::string & from,
-        const std::string & to);
-
-struct gpt_vocab {
-    using id    = int32_t;
-    using token = std::string;
-
-    std::map<token, id> token_to_id;
-    std::map<id, token> id_to_token;
-    std::vector<std::string> special_tokens;
-
-    void add_special_token(const std::string & token);
-};
-
-// poor-man's JSON parsing
-std::map<std::string, int32_t> json_parse(const std::string & fname);
-
-std::string convert_to_utf8(const std::wstring & input);
-
-std::wstring convert_to_wstring(const std::string & input);
-
-void gpt_split_words(std::string str, std::vector<std::string>& words);
-
-// split text into tokens
-//
-// ref: https://github.com/openai/gpt-2/blob/a74da5d99abaaba920de8131d64da2862a8f213b/src/encoder.py#L53
-//
-// Regex (Python):
-// r"""'s|'t|'re|'ve|'m|'ll|'d| ?\p{L}+| ?\p{N}+| ?[^\s\p{L}\p{N}]+|\s+(?!\S)|\s+"""
-//
-// Regex (C++):
-// R"('s|'t|'re|'ve|'m|'ll|'d| ?[[:alpha:]]+| ?[[:digit:]]+| ?[^\s[:alpha:][:digit:]]+|\s+(?!\S)|\s+)"
-//
-std::vector<gpt_vocab::id> gpt_tokenize(const gpt_vocab & vocab, const std::string & text);
-
-// test outputs of gpt_tokenize
-//
-//   - compare with tokens generated by the huggingface tokenizer
-//   - test cases are chosen based on the model's main language (under 'prompt' directory)
-//   - if all sentences are tokenized identically, print 'All tests passed.'
-//   - otherwise, print sentence, huggingface tokens, ggml tokens
-//
-void test_gpt_tokenizer(gpt_vocab & vocab, const std::string & fpath_test);
-
-// load the tokens from encoder.json
-bool gpt_vocab_init(const std::string & fname, gpt_vocab & vocab);
-
-// sample next token given probabilities for each embedding
-//
-//   - consider only the top K tokens
-//   - from them, consider only the top tokens with cumulative probability > P
-//
-// TODO: not sure if this implementation is correct
-// TODO: temperature is not implemented
-//
-gpt_vocab::id gpt_sample_top_k_top_p(
-        const gpt_vocab & vocab,
-        const float * logits,
-        int    top_k,
-        double top_p,
-        double temp,
-        std::mt19937 & rng);
-
-gpt_vocab::id gpt_sample_top_k_top_p_repeat(
-        const gpt_vocab & vocab,
-        const float * logits,
-        const int32_t * last_n_tokens_data,
-        size_t last_n_tokens_data_size,
-        int    top_k,
-        double top_p,
-        double temp,
-        int repeat_last_n,
-        float repeat_penalty,
-        std::mt19937 & rng);
-
-//
 // Audio utils
 //
 
 // Check if a buffer is a WAV audio file
 bool is_wav_buffer(const std::string buf);
 
-// Read WAV audio file and store the PCM data into pcmf32
-// fname can be a buffer of WAV data instead of a filename
-// The sample rate of the audio must be equal to COMMON_SAMPLE_RATE
-// If stereo flag is set and the audio has 2 channels, the pcmf32s will contain 2 channel PCM
-bool read_wav(
-        const std::string & fname,
-        std::vector<float> & pcmf32,
-        std::vector<std::vector<float>> & pcmf32s,
-        bool stereo);
-
 // Write PCM data into WAV audio file
 class wav_writer {
 private:
@@ -185,7 +58,7 @@
     // It is assumed that PCM data is normalized to a range from -1 to 1
     bool write_audio(const float * data, size_t length) {
         for (size_t i = 0; i < length; ++i) {
-            const int16_t intSample = int16_t(data[i] * 32767);
+            const int16_t intSample = data[i] * 32767;
             file.write(reinterpret_cast<const char *>(&intSample), sizeof(int16_t));
             dataSize += sizeof(int16_t);
         }
@@ -286,12 +159,27 @@
 // Terminal utils
 //
 
+static std::string set_xterm256_foreground(int rgb) {
+    int x = rgb2xterm256(rgb);
+    std::ostringstream oss;
+    oss << "\033[38;5;" << x << "m";
+    return oss.str();
+}
 
-// Terminal color map. 10 colors grouped in ranges [0.0, 0.1, ..., 0.9]
-// Lowest is red, middle is yellow, highest is green.
+static inline int rgb(int red, int green, int blue) {
+    return (red & 255) << 16 | (green & 255) << 8 | (blue & 255);
+}
+
+// Lowest is red, middle is yellow, highest is green. Color scheme from
+// Paul Tol; it is colorblind friendly https://personal.sron.nl/~pault/
 const std::vector<std::string> k_colors = {
-    "\033[38;5;196m", "\033[38;5;202m", "\033[38;5;208m", "\033[38;5;214m", "\033[38;5;220m",
-    "\033[38;5;226m", "\033[38;5;190m", "\033[38;5;154m", "\033[38;5;118m", "\033[38;5;82m",
+    set_xterm256_foreground(rgb(220,   5,  12)),
+    set_xterm256_foreground(rgb(232,  96,  28)),
+    set_xterm256_foreground(rgb(241, 147,  45)),
+    set_xterm256_foreground(rgb(246, 193,  65)),
+    set_xterm256_foreground(rgb(247, 240,  86)),
+    set_xterm256_foreground(rgb(144, 201, 135)),
+    set_xterm256_foreground(rgb( 78, 178, 101)),
 };
 
 //
